International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004
0.36
0.33
| 0.30
0.27
0.24
0.21
0.18
] 9.15
0.12
0.09
0.06
0.03
0.00
raa
180°
e
e
LO
45.0
37.5
30.0
Figure 6: Modelled NIR reflectance for olive grows where
NIR - VIS = (NIR — VIS) mean — (NIR — VIS)stddev
e ed
x
S,
\ 0.36
0.33
0.30
0.27
0.24
0.21
0.18
0.15
0.12
0.09
0.06
| 0.03
* 0.00
52.5
45.0
37.5
30.0
22.5
15.0
7:5
0.0
vza
Figure 7: Modelled NIR reflectance for olive grows where
NIR - VIS = (NIR — VIS) eus + (NIR —- VIS) die
4 CONCLUSIONS
It has been shown that the NTAM possesses a big potential to
reduce BRDF effects in AVHRR imagery of Spain. This is
quantitatively expressed by the good results in model inversion
for the two channels and on practically all land cover classes.
Apart from the good results, the main advantages of the NTAM
are its physical foundations and its simplicity, as only one set of
parameters for land cover class and channel has to be provided
to correct for the whole vegetation period.
The derived correction parameters offer a great potential for
interpretation of land cover specific biophysical properties.
Results of the forward mode of BRDF correction are not
discussed in this paper. Future work should address the
transition pixel problem which is enhanced in the forward mode
of BRDF correction. As landscape in Spain is obviously
structured on a larger scale than Canada, the land cover based
approach is to be further investigated.
REFERENCES
Aguado, I., Chuvieco, E. Martín, P. Salas, FJ. 2003.
Assessment of forest fire danger conditions in southern Spain
from NOAA images and meteorological indices. International
Journal for Remote Sensing. 24. 1653 -1668
Chen, J.M., Cihlar, J. 1997. A hotspot function in a simple
bidirectional reflectance model for satellite applications.
Journal of Geophysical Research. 102. 25907-25913
Chuvieco, E. 2002. Teledetección ambiental. ^ Ariel
CienciaChuvieco, E., Aguado, IL, Cocero, D., Riano, D. 2003.
Design of an empirical index to estimate fuel moisture content
from NOAA-AVHRR analysis in forest fire danger studies.
International Journal of Remote Sensing. 24. 1621-1637 .
44
Cihlar, J., Chen, J., Li, Z., Latifovic, R., Fedosejevs, G., Adair,
M., Parl, W., Fraser, R., Trishenko, A., Guindon, B., Stanley,
D., Morse, D. 2002. GeoComp-n, an advanced system for the
processing of coarse and medium resolution satellite data. Part
2: Biophysical products for Northern ecosystems. Canadian
Journal for Remote Sensing. 28. 21-44
Chopping, M.J. 2000. Large-scale BRDF retrieval over New
Mexico with a multiangular NOAA AVHRR dataset. Remote
Sensing of Environment. 74. 163-191
CORINE Land Cover Report - From land cover to landscape
diversity. 2000. DG AGRI, EUROSTAT, the Joint Research
Centre (Ispra) and the European Environmental Agency
Cracknell, A. 1997. The Advanced Very High Resolution
Radiometer (AVHRR). Taylor and Francis
Dymond, J.R., Shepherd, J.D., Qi, J. 2001. A simple physical
model of vegetation for standardising optical satellite imagery.
Remote Sensing of Environment. 77. 230-239
Hu, B., Lucht, W., Strahler, A.H., Schaaf, C.B., Smith, M.
2000. Surface albedos and angle corrected NDVI from
AVHRR observations of South America. Remote Sensing of
Environment. 71. 119-132
KIM User's Guide. 2000. Edited by: GOODRUM, G.,
KIDWELL, K.B., WINSTON, W. National Oceanic and
Atmospheric Administration. Suitland, MD 20746-4304
Latifovic, R., Cihlar, J., Chen, J. 2003. A comparison of
BRDF models for the normalisation of satellite optical data to a
standard sun-sensor-target geometry. [EEE Transactions on
Geoscience and Remote Sensing. 8. 1889-1898
Leroy, M., Roujean, J.L. 1994. Sun and view angle corrections
on reflectance derived from NOAA AVHRR data. IEEE
Transactions on Geoscience and Remote Sensing. 32(3). 684-
697